AI Platform Prediction can host your models so you can get predictions from them in the cloud. The process of hosting a saved model is called deployment. The prediction service manages the infrastructure necessary to run the model at scale and makes it available for online and batch prediction requests. Prediction using machine learning, or prediction in the field of machine learning, refers to the result of an algorithm that has been trained on a set of historical data.
The algorithm then generates probable values for unknown variables in each record of the new data. The purpose of prediction in machine learning is to project a set of probable data that relates to the original data. This helps organizations predict future customer behavior and changes in the market. Basically, prediction is used to fit the data as closely as possible.
With machine learning predictions, organizations make proactive decisions to avoid the expected loss of users. To achieve maximum success with prediction in machine learning, organizations must have an infrastructure that supports the solutions and high quality data to deliver the algorithm.
